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At least 379 records · Page 21

Three-state harmonic models for photoinduced charge transfer

A widely used strategy for simulating the charge transfer between donor and acceptor electronic states in an all-atom anharmonic condensedphase system is based on invoking linear response theory to describe the system in terms of an effective spin-boson model Hamiltonian. Extending this strategy to photoinduced charge transfer processes requires also taking into consideration the ground electronic state in addition to the excited donor and acceptor electronic states. In this paper, we revisit the problem of describing such nonequilibrium processes in terms of an effective three-state harmonic model. We do so within the framework of nonequilibrium Fermi’s golden rule (NE-FGR) in the context of photoinduced charge transfer in the carotenoid–porphyrin–C 60 (CPC 60 ) molecular triad dissolved in explicit tetrahydrofuran (THF). To this end, we consider different ways for obtaining a three-state harmonic model from the equilibrium autocorrelation functions of the donor–acceptor, donor–ground, and acceptor–ground energy gaps, as obtained from all-atom molecular dynamics simulations of the CPC 60 /THF system. The quantum-mechanically exact time-dependent NE-FGR rate coefficients for two different charge transfer processes in two different triad conformations are then calculated using the effective three-state model Hamiltonians as well as a hierarchy of more approximate expressions that lead to the instantaneous Marcus theory limit. Our results show that the photoinduced charge transfer in CPC 60 /THF can be described accurately by the effective harmonic three-state models and that nuclear quantum effects are small in this system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Two-dimensional electronic–vibrational spectroscopy: Exploring the interplay of electrons and nuclei in excited state molecular dynamics

Two-dimensional electronic-vibrational spectroscopy (2DEVS) is an emerging spectroscopic technique which exploits two different frequency ranges for the excitation (visible) and detection (infrared) axes of a 2D spectrum. In contrast to degenerate 2D techniques, such as 2D electronic or 2D infrared spectroscopy, the spectral features of a 2DEV spectrum report cross correlations between fluctuating electronic and vibrational energy gaps rather than autocorrelations as in the degenerate spectroscopies. The center line slope of the spectral features reports on this cross correlation function directly and can reveal specific electronic-vibrational couplings and rapid changes in the electronic structure, for example. The involvement of the two types of transition moments, visible and infrared, makes 2DEVS very sensitive to electronic and vibronic mixing. 2DEV spectra also feature improved spectral resolution, making the method valuable for unraveling the highly congested spectra of molecular complexes. The unique features of 2DEVS are illustrated in this paper with specific examples and their origin described at an intuitive level with references to formal derivations provided. Although early in its development and far from fully explored, 2DEVS has already proven to be a valuable addition to the tool box of ultrafast nonlinear optical spectroscopy and is of promising potential in future efforts to explore the intricate connection between electronic and vibrational nuclear degrees of freedom in energy and charge transport applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Representations and strategies for transferable machine learning improve model performance in chemical discovery

Strategies for machine-learning (ML)-accelerated discovery that are general across material composition spaces are essential, but demonstrations of ML have been primarily limited to narrow composition variations. By addressing the scarcity of data in promising regions of chemical space for challenging targets such as open-shell transition-metal complexes, general representations and transferable ML models that leverage known relationships in existing data will accelerate discovery. Over a large set (~1000) of isovalent transition-metal complexes, we quantify evident relationships for different properties (i.e., spin-splitting and ligand dissociation) between rows of the Periodic Table (i.e., 3d/4d metals and 2p/3p ligands). We demonstrate an extension to the graph-based revised autocorrelation (RAC) representation (i.e., eRAC) that incorporates the group number alongside the nuclear charge heuristic that otherwise overestimates dissimilarity of isovalent complexes. To address the common challenge of discovery in a new space where data are limited, we introduce a transfer learning approach in which we seed models trained on a large amount of data from one row of the Periodic Table with a small number of data points from the additional row. We demonstrate the synergistic value of the eRACs alongside this transfer learning strategy to consistently improve model performance. Analysis of these models highlights how the approach succeeds by reordering the distances between complexes to be more consistent with the Periodic Table, a property we expect to be broadly useful for other material domains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An analytic and complete equation of state for condensed phase materials

Analytic equations of state (EOS) are intended to reproduce theoretical and experimental data in a single phase portion of the thermodynamic space. We devise a complete and thermodynamically consistent model with four distinct features: (1) a reference isotherm that remains thermodynamically stable, (2) a flexible specific heat model based on a fourth-order rational polynomial, (3) a Grüneisen parameter that depends on specific volume and temperature, and (4) pressure and internal energy functions that can be inverted analytically in temperature. The model aims to improve the accuracy of existing equations of state while remaining computationally efficient. To demonstrate its features, we include calibrations for single-crystal pentaerythritol tetranitrate (PETN), liquid nitromethane (NM), and hexagonal close-packed beryllium (Be) metal. The parameter optimization uses the specific heat capacity, Grüneisen parameter, and static compression curves obtained from density functional theory for the crystalline solids and molecular dynamics simulations for liquid NM. We also present a velocity autocorrelation function that yields accurate phonon densities of states for the EOS calibration from the molecular dynamics trajectories. Each of the three calibrations is constrained to enforce the ambient state from experimental measurements and validated against experimental Hugoniot data from multiple sources. We also include one-dimensional hydrodynamic simulations of the isentropic compression experiments for beryllium conducted at the Z facility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A DFT-based kinetic Monte Carlo simulation of multiphase oxide-metal thin film growth

Functional thin films of nanoscale metal pillars in oxide or nitride matrices known as vertically aligned nanocomposite (VAN) have gained much interest owing to their unique strain-coupled and highly anisotropic properties. So far, the deposition of these films has been explored mostly experimentally. In this work, a density functional theory (DFT)-based kinetic Monte Carlo simulation model using Bortz–Kalos–Lebowitz algorithm was developed to understand the growth of VAN films deposited by pulsed laser technique on mismatching substrates. The model has been parameterized and applied to understand the kinetics of growth thin films consisting of Au pillars in CeO2 matrix deposited on SrTiO3 substrates. The effects of pulsed laser deposition (PLD) conditions including the pulse frequency, deposition flux, and substrate temperature were explored. The simulations indicate that the Au pillar size and shape exhibit significant dependence on the PLD conditions. Namely, increasing the temperature increases the average pillar size and lowers the pillar density, and vice versa. In addition, the simulations revealed that increasing the deposition rate results in lowering the average pillar size and increasing the density. Particularly, the DFT results suggest that Au pillar size can be tuned during the initial growth of the first monolayer due to the significantly low activation barrier. Our analysis showed that the relationship between the average pillar size and pillar density is influenced by the kinetics. Furthermore, autocorrelation analysis showed that pillars self-organize in quasi-ordered patterns at certain windows of the deposition conditions, which is attributed to the complex nature of the chemical interactions in the system, the kinetics, and the deposition parameters.

Physics↗

Mean force emission theory for classical bremsstrahlung in strongly coupled plasmas

This work presents mean force emission theory, which extends the classical theory of bremsstrahlung emission to strongly coupled plasmas. In the high-frequency limit, the theory reduces to solving for the electron trajectory during a binary collision, but where the electron–ion interactions occur through the potential of mean force. In the low-frequency limit, it uses an autocorrelation formalism that captures effects of multiple collisions and strongly correlated motion. The predictions are benchmarked by comparison with first-principles classical molecular dynamics simulations of a fully ionized hydrogen plasma in which all interactions are repulsive. The comparison shows good agreement up to Coulomb coupling strengths of Γ∼30. The theory improves upon traditional models by including strong coupling effects and systematically including the effect of multiple collisions. Furthermore, mean force emission theory provides evidence that the Drude correction factor commonly used in quantum calculations of optical quantities may not be adequate at strong coupling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Light scattering by V 4 O 7 film across the metal–insulator transition

The experimental study of the angle-resolved hemispherical light scattering by V 4 O 7 film within a broad temperature range across metal–insulator transition reveals complex structural reorganization of the film deposited on the c-cut sapphire crystal. The bidirectional scattering distribution function and the surface autocorrelation function were obtained from scattering data to visualize statistics of the spatially resolved contributions of optical inhomogeneities in normal and lateral directions to the surface. The measurements reveal an anisotropic surface roughness distribution due to the twinned domain structure, with significant anisotropy changes across the phase transition. The V 4 O 7 film deposited on sapphire leads to a polydomain structure, minimizing elastic strain energy with distinct multiscale distributions of surface domains. Near T c , the material shows the lowest roughness but the highest lateral disorder of the surface.

36 MATERIALS SCIENCE↗

A generative artificial intelligence framework for long-time plasma turbulence simulations

Generative deep learning techniques are employed in a novel framework for the construction of surrogate models capturing the spatiotemporal dynamics of 2D plasma turbulence. The proposed Generative Artificial Intelligence Turbulence (GAIT) framework enables the acceleration of turbulence simulations for long-time transport studies. GAIT leverages a convolutional variational auto-encoder and a recurrent neural network to generate new turbulence data from existing simulations, extending the time horizon of transport studies with minimal computational cost. The application of the GAIT framework to plasma turbulence using the Hasegawa–Wakatani (HW) model is presented, evaluating its performance via various analyses. Very good agreement is found between the GAIT and the HW models in the spatiotemporal Fourier and Proper Orthogonal Decomposition spectra, the flow topology characterized by the Okubo–Weiss parameter, and the time autocorrelation function of turbulent fluctuations. Excellent agreement has also been obtained in the probability distribution function of particle displacements and the effective turbulent diffusivity. In-depth analyses of the latent space of turbulent states, choice of hyperparameters and alternative deep learning models for the time prediction are presented. Our results highlight the potential of Artificial Intelligence-based surrogate models to overcome the computational challenges in turbulence simulation, which can be extended to other situations such as geophysical fluid dynamics.

Artificial intelligence↗

Extended molecular eigenmodes treatment of dipole–dipole NMR relaxation in real fluids

Traditional models of NMR relaxation fail to account for the complex, multi-exponential behavior of the autocorrelation function in realistic systems characterized by soft-interactions and molecules that are chemically and physically complex. Here, in this study, we describe the relative diffusion of the spin dipoles by means of a Fokker–Planck equation that includes an interaction potential of mean force to account for the response of the physical/chemical environment around the dipoles. By numerically solving the Fokker–Planck equation for the diffusion propagator, we estimate dipole–dipole NMR relaxation for like- and unlike-spin systems via its eigenmode solution. We test the model against molecular simulations of diffusing dipoles with harmonic potentials and also validate using experimental longitudinal relaxation data from real systems, including Gd(III)–aqua and Gd(III)–DO3A–butrol complexes, the latter being an important MRI contrast agent. Using this novel approach, we predict both the inner- and outer-shell contributions to the relaxivity rates with excellent accuracy at frequencies relevant to MRI. We also show that, under the appropriate assumptions, our framework naturally recovers the Bloembergen–Purcell–Pound, the Solomon–Bloembergen–Morgan, and the Hwang–Freed models. Our implementation is general and publicly available for application to a broad range of systems.

Pinheiro dos Santos, Thiago J. [Rice Univ., Housto↗

Out-of-time-order correlators bridge classical transport and quantum dynamics

The out-of-time-order correlator (OTOC) has emerged as a central tool for quantifying decoherence across wide-ranging physical platforms. Here, we demonstrate its direct measurement in a classical ensemble using nuclear magnetic resonance with a modulated gradient spin echo sequence and extend the method into a multidimensional correlation to track exchange phenomena. Position is encoded through magnetic field gradients and momentum through the velocity autocorrelation function, enabling experimental access to OTOCs for proton motion confined within the self-similar lattice of the metal–organic framework MOF-808. Here, water confined to specified geometries within the MOF pores gives rise to spatially distinct diffusive eigenmodes with characteristic relative entropies. We demonstrate that periodic radio frequency driving combined with gradient modulation yields entropy evolution through the selection of distinct diffusion modes. Frequency-resolved diffusion spectra connect these entropy dynamics to classical heat exchange laws, revealing how operational features of quantum systems are mirrored in confined, macroscopic spin ensembles.

Fricke, Sophia N. [University of California, Berke↗

Picosecond lasing in ytterbium fibre laser with nonlinear optical loop mirror: experiment and numerical simulation

The operation regimes of a pulsed all-normal-dispersion polarisation-maintaining fibre laser with a nonlinear optical loop mirror are studied. The use of polarisation-maintaining fibres ensures polarisation and temperature stability of output radiation. The lasing and instability thresholds of the pulsed laser are determined experimentally. A spectral filter placed in the cavity makes it possible to change the centre wavelength of laser radiation within the range 1.02 – 1.05 μm with a spectral full width at half maximum of 2 nm. The average output power is 7 mW, which corresponds to a pulse energy of 0.8 nJ. The autocorrelation function width of the output pulse is 50 ps. The minimum pulse duration achieved after compression by an external pair of diffraction gratings is 1.8 ps. The dynamics of the temporal and spectral parameters of laser pulses is studied using mathematical simulation based on numerical solution of the nonlinear Schrödinger equation. The simulation results coincide with experimental data with a high accuracy. (lasers)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Influence of low concentrations of scatterers and signal detection time on the results of their measurements using dynamic light scattering

The influence of limited detection time on the form of the autocorrelation function (ACF) has been analysed for measurements in low-concentration suspensions by dynamic light scattering with allowance for the spatial distribution of the laser beam intensity. The general view of the ACF of the scattered light intensity is obtained for a Gaussian beam and a finite measurement time. The results of the theoretical analysis are compared with the experimental data and the results obtained by computer simulation of the scattering from an ensemble of particles involved in Brownian motion in a Gaussian beam. It is shown that, in the case of low suspension concentrations, the ACF distortions related to finite detection time lead to underestimation of the particle sizes and occurrence of an artefact peak in the distribution of the scattered light intensity over scatterer sizes. An empirical dependence of the measured size of particles on their number in the scattering volume is found. (light scattering)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spectral and temporal dynamics of ultrashort pulses in a holmium-doped fibre amplifier

We have optimised a hybrid mode-locked holmium-doped fibre laser and a holmium-doped fibre amplifier for obtaining stable pulses as short as possible. Temporal and spectral characteristics of pulsed light have been measured as functions of pump power. Lasing has been achieved in the wavelength range 2066 – 2068 nm, with a full width at half maximum of the emission spectrum from 3 to 4 nm. The pulse duration does not exceed 1 ps and the pulse energy ranges from 0.2 to 0.5 nJ. To raise the pulse energy, holmium-doped fibre amplifiers based on two types of active fibre have been used. We have demonstrated a decrease in the width of the central part of the pulse autocorrelation function and considerable broadening of the spectrum of the pulses. The maximum average power at the amplifier output exceeds 200 mW. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cavity molecular dynamics simulations of liquid water under vibrational ultrastrong coupling

We simulate vibrational strong coupling (VSC) and vibrational ultrastrong coupling (V-USC) for liquid water with classical molecular dynamics simulations. When the cavity modes are resonantly coupled to the O–H stretch mode of liquid water, the infrared spectrum shows asymmetric Rabi splitting. The lower polariton (LP) may be suppressed or enhanced relative to the upper polariton (UP) depending on the frequency of the cavity mode. Furthermore, although the static properties and the translational diffusion of water are not changed under VSC or V-USC, we do find the modification of the orientational autocorrelation function of H 2 O molecules especially under V-USC, which could play a role in ground-state chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Popnet : computer vision based deep learning model for forecasting gridded population

Here, this study introduces Popnet, a deep learning model for forecasting 1 km-gridded populations, integrating U-Net, ConvLSTM, a Spatial Autocorrelation module and deep ensemble methods. Using spatial variables and population data from 2000 to 2020, Popnet predicts South Korea’s population trends by age groups (under 14, 15-64 and over 65) up to 2040. In validation, it outperforms traditional machine learning and state-of-the-art computer vision models. The output of this model discovered significant polarisation: population growth in urban areas, especially the capital region, and severe depopulation in rural areas. Popnet is a robust tool for offering significant insights to policymakers and related stakeholders about the detailed future population, which allows them to establish detailed, localised planning and resource allocations.

computer vision↗

A coarse-grained computational model of the nuclear pore complex predicts Phe-Gly nucleoporin dynamics

The phenylalanine-glycine–repeat nucleoporins (FG-Nups), which occupy the lumen of the nuclear pore complex (NPC), are critical for transport between the nucleus and cytosol. Although NPCs differ in composition across species, they are largely conserved in organization and function. Transport through the pore is on the millisecond timescale. Here, to explore the dynamics of nucleoporins on this timescale, we use coarse-grained computational simulations. These simulations generate predictions that can be experimentally tested to distinguish between proposed mechanisms of transport. Our model reflects the conserved structure of the NPC, in which FG-Nup filaments extend into the lumen and anchor along the interior of the channel. The lengths of the filaments in our model are based on the known characteristics of yeast FG-Nups. The FG-repeat sites also bind to each other, and we vary this association over several orders of magnitude and run 100-ms simulations for each value. The autocorrelation functions of the orientation of the simulated FG-Nups are compared with in vivo anisotropy data. We observe that FG-Nups reptate back and forth through the NPC at timescales commensurate with experimental measurements of the speed of cargo transport through the NPC. Our results are consistent with models of transport where FG-Nup filaments are free to move across the central channel of the NPC, possibly informing how cargo might transverse the NPC.

59 BASIC BIOLOGICAL SCIENCES↗

Periodicity of the solar full-disk magnetic fields

A full-disk solar magnetogram has been measured each day since 1970 January 19, and the daily Magnetic Plage Strength Index (MPSI) and the daily Mount Wilson Sunspot Index (MWSI) were calculated for each magnetogram at the Mount Wilson Observatory. The MPSI and MWSI are used to investigate the periodicity of the solar full-disk magnetic activity through autocorrelation analyses. Just two periods, the solar cycle and the rotation cycle, are determined in both the MPSI (the solar full-disk weak magnetic field activity) and MWSI (the solar full-disk strong magnetic field activity) with no annual signal found. The solar cycle for MPSI (10.83 yr) is found to be obviously longer than that for MWSI (9.77 yr). The rotation cycle is determined to be 26.8 ± 0.63 sidereal days for MPSI and 27.4 ± 2.4 sidereal days for MWSI. The rotation cycle length for MPSI is found to fluctuate around 27 days within a very small amplitude, but for MWSI it obviously temporally varies with a rather large amplitude. The rotation cycle for MWSI seems longer near solar minimum than at solar maximum. Cross-correlation analyses of daily MPSI and MWSI are carried out, and it is inferred that the MPSI components partly come from relatively early MWSI measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

Observation of discrete oscillations in a model-independent plot of cosmological scale factor versus lookback time and scalar field model

We have observed damped longitudinal cosmological-scale oscillations in a unique model-independent plot of scale factor against lookback time for Type Ia supernovae data. We found several first-derivative relative maxima/minima spanning the range of reported transition redshifts. These extrema comprise two full cycles with a period of approximately 0.15 Hubble times (H{sub 0}=68 km s{sup −1} Mpc{sup −1}). This period corresponds to a fundamental frequency of approximately seven cycles over the Hubble time. Transition-z values quoted in the literature generally fall near these minima and may explain the reported wide spread up to the predicted ΛCDM value of approximately z = 0.77. We also observe second and third harmonics of the fundamental. The scale factor data is analyzed several different ways, including smoothing, Fourier transform, and autocorrelation. We propose a cosmological scalar field harmonic oscillator model for the observation. On this timescale, for a quantum scalar field, the scalar field mass is extraordinarily small at 3 × 10{sup −32} eV. Our scalar field density parameter precisely replaces the ΛCDM dark matter density parameter in the Friedmann equations, resulting in essentially identical data fits, and its present value matches the Planck value. Thus the wave is fundamentally a dark matter wave. We therefore posit that this scalar field manifests itself as the dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗